Informatica MDM Interview Questions

Last updated on Nov 22, 2023

Informatica MDM is a widely used Master Data Management tool, offering a unified platform for organizing and managing data safely and reliably. It provides insights into customer and product relationships, aiding in effective data management for business success. The following list includes common Informatica MDM interview questions, ranging from beginner to advanced levels.

Most Frequently Asked Informatica MDM Interview Questions and Answers

1. Explain about MDM?

Ans. Master Data Management (MDM) is a strategic approach employed by organizations to consolidate critical data into a unified master file, often referred to as the master data. This master data serves as a pivotal reference point for key business decisions, enabling consistent data sharing across various departments.

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2. What does the term MDM mean?

Ans. MDM, or Master Data Management, denotes a holistic technique vital for enterprises in centralizing their crucial data into a single master file. This master file acts as a foundational reference point and enhances data coherence across various organizational sectors.

3. List out different components of Powercenter?

Ans. PowerCenter, a robust data integration tool, comprises several key components such as the Metadata Manager, PowerCenter Domain, Repository Service, Administration Console, Integration Service, PowerCenter Repository Reports, PowerCenter Client, Web Services Hub, and the Data Analyzer.

4. Explain to us about Data Warehousing?

Ans. Data Warehousing encompasses the collection and management of data from diverse sources, aiding organizations in deriving insightful analysis. It involves the integration of various technologies and components, facilitating structured data utilization for informed decision-making.

5. Explain to us about various fundamental phases of data warehousing?

Ans. Data Warehousing evolves through several phases: Offline Operational Databases, Offline Data Warehouse, Real-time Data Warehouse, and Integrated Data Warehouse. Each phase represents a distinct stage in data processing and management, contributing to efficient business operations.

6. What are the most significant technical and management challenges in adopting MDM?

Ans. Adopting MDM involves navigating both technical and managerial hurdles. Technically, it's about ensuring the seamless integration of diverse data sets. From a management perspective, the challenge lies in demonstrating the tangible ROI of MDM initiatives to stakeholders.

7. What is meant by Dimensional Modelling?

Ans. Dimensional Modelling in data warehousing is characterized by its distinct structure, separating it from the third normal form. It primarily consists of two types of tables: fact tables, which measure business processes, and dimension tables, providing context to these measurements.

8. What is meant by dimension table?

Ans. A dimension table in data warehousing is a collection of hierarchies, categories, and logic. These tables play a crucial role in facilitating deeper analysis by allowing users to navigate through various hierarchy levels.

9. Explain various methods to load the data in dimension tables?

Ans. Data loading into dimension tables can be done using two primary methods: the Conventional (Slow) method, where data integrity checks are performed before loading, and the Direct (Fast) method, where constraints are temporarily bypassed for swift data loading.

10. Define fact tables?

Ans. In the context of data warehousing, a fact table is a central entity characterized by its storage of quantitative data and metrics related to business processes. It's linked to dimension tables through foreign keys and forms the core of the star or snowflake schema.

11. Explain the term Mapping?

Ans. Mapping in data integration refers to the process of defining the data flow between source and target systems. It involves a set of rules and transformations that dictate how data is to be converted and formatted during the transfer process.

12. Define Mapplet?

Ans. A Mapplet in Informatica PowerCenter is a reusable object comprising a set of transformations. It allows the reuse of transformation logic in multiple mappings, thereby enhancing efficiency and consistency across data integration processes.

13. Explain to us about Transformation?

Ans. Transformation in data integration contexts is a process where data is modified and refined. In Informatica, a transformation is a repository object that performs operations on data, facilitating its movement and modification according to business rules.

14. What is Data Mining?

Ans. Data Mining involves extracting valuable insights from large datasets. It employs sophisticated algorithms to uncover hidden patterns and relationships, assisting in areas such as market analysis, fraud detection, and scientific discovery.

15. List out various objects that cannot be used in the Mapplets?

Ans. In Informatica, certain objects are incompatible with Mapplets, including COBOL source definitions, Normalizer transformations, Joiner transformations, non-reusable sequence generator transformations, and a few others.

16. What are the foreign columns in fact and dimensional tables?

Ans. In data warehousing, foreign keys in fact tables correspond to primary keys in dimension tables. Conversely, in dimension tables, foreign keys typically link to primary keys in entity tables, establishing a relational structure.

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17. Explain different ways used in Informatica to switch one environment to another?

Ans. Transitioning between environments in Informatica can be achieved through methods like copying folders/objects, exporting and importing repository data, and utilizing deployment groups or XML dumps of mappings.

18. Differentiate Mapping variables and Mapping parameters?

Ans. Mapping variables in Informatica are dynamic, changing during a session, while mapping parameters are static, set before a session starts and remaining constant throughout its duration.

19. Explain various ways to eliminate duplicate records from Informatica?

Ans. In Informatica, duplicates can be removed by employing strategies like using the 'select distinct' option in the source qualifier, applying SQL queries with specific conditions, or grouping and aggregating fields.

20. How to find invalid mappings in a folder?

Ans. Invalid mappings within a folder in Informatica can be identified using a specific SQL query that checks for mappings not validated against the repository's criteria.

21. Explain different repositories that can be created using the Informatica Repository Manager?

Ans. Various types of repositories can be established using Informatica Repository Manager, including Standalone Repositories for independent operations, Global Repositories for centralized object sharing, and Local Repositories for domain-specific operations.

22. Explain different data movement modes that are available in Informatica Server?

Ans. Informatica Server supports two primary data movement modes: ASCII Mode for standard character data processing and Unicode Mode for handling diverse character sets, facilitating global data integration practices.

23. Explain different types of Locks that are used in Informatica MDM 10.1?

Ans. In Informatica MDM 10.1, locks are used to manage data access and modifications. Exclusive Locks restrict access to a single user, while Write Locks allow multiple users to concurrently modify the underlying metadata.

24. List out the tools that do not require Lock-in Informatica MDM?

Ans. Certain tools in Informatica MDM, such as the Hierarchy Manager, Data Manager, Merge Manager, and Audit Manager, operate without requiring a lock mechanism, streamlining certain data management tasks.

25. List out the tools that require Lock in Informatica MDM?

Ans. In Informatica MDM, tools like Message Queues, Users, Databases, Tool Access, and Security Providers require locks for making configuration changes to ensure data integrity and controlled access.

26. Explain about OLAP and OLTP?

Ans. OLAP (Online Analytical Processing) and OLTP (Online Transaction Processing) are two distinct types of data processing systems. OLAP is used for complex analytical queries, while OLTP is designed for managing daily transactional data in businesses.

27. What is the expiration module of automatic look in Informatica MDM?

Ans. In Informatica MDM, the automatic lock expiration module ensures that locks on data records expire after a set period, typically after 60 seconds, to maintain data flow and prevent prolonged data access blocking.

28. Explain various components of the Informatica hub console?

Ans. The Informatica hub console is composed of various components such as the Design Console for deployment configurations, Data Steward Console for data review, and Administration Console for database administration and security management.

29. List the tables that can linked to the staging date?

Ans. In Informatica MDM, staging data can be linked to various tables like Raw Table, Staging Table, Landing Table, and Rejects Table, each serving a specific purpose in the data integration process.

30. Tell us about various loading phases in MDM?

Ans. The loading phases in MDM include Land, Stage, Load, Match, and Consolidate. Each phase represents a step in the data management process, from initial data capture to final data consolidation and integration.

31. Tell us about the Informatica Powercenter?

Ans. Informatica Powercenter is a prominent ETL (Extract, Transform, Load) tool used for building enterprise data warehouses. It efficiently handles data extraction from multiple sources, transformation according to business needs, and loading into target systems.

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32. Describe all the biggest management and technical challenges in adopting MDM?

Ans. Adopting MDM presents challenges like ensuring Model Agility for flexible data management, implementing robust Data Governance for quality control, setting suitable Data Standards, ensuring accurate Data Integration, and maintaining effective Data Stewardship.

33. What is Data Warehousing?

Ans. Data Warehousing involves the collection, storage, and management of large volumes of business data. It serves as a crucial component for decision-making processes by facilitating comprehensive data analysis and query execution.

34. Define Dimensional Modeling?

Ans. Dimensional Modeling is a data structuring technique used in data warehousing. It involves organizing data into Fact tables, which store business metrics, and Dimension tables, which provide context and additional calculations.

35. Describe various fundamental stages of Data Warehousing?

Ans. Data Warehousing progresses through stages like Offline Operational Databases, Offline Data Warehouse, Real-time Data Warehouse, and Integrated Data Warehouse. Each stage represents a development in data storage and processing for business intelligence.

36. Define Informatica PowerCenter.

Ans. Informatica PowerCenter is an ETL tool used for building data warehouses. It streamlines the process of data extraction, transformation, and loading, and includes components like client tools, a server, a repository, and a repository server.

37. Name various components of Informatica PowerCenter.

Ans. Key components of Informatica PowerCenter include the PowerCenter Repository, Domain, Client, Administration Console, Integration Service, Repository Service, Data Analyzer, Web Services Hub, and PowerCenter Repository Reports.

38. What is Mapping?

Ans. Mapping in Informatica involves defining how data flows from sources to targets. It includes setting up transformations and rules for data manipulation and conversion during the integration process.

39. What is a Mapplet?

Ans. A Mapplet in Informatica is a reusable set of transformations that can be employed in multiple mappings. It facilitates the reuse of established data processing logic, enhancing efficiency and consistency.

40. What is Transformation?

Ans. Transformation in Informatica refers to the modification of data during the ETL process. It encompasses a range of operations that adapt and refine data, ensuring it meets business requirements and objectives.

41. What is Data Mining?

Ans. Data Mining, or Knowledge Discovery in Data (KDD), involves analyzing extensive data sets to extract hidden patterns, relationships, and insights. It's crucial for discovering valuable information that can guide business strategies and decisions.

42. What is a Fact Table?

Ans. In data warehousing, a fact table is central to a star schema and contains quantitative data related to business processes. It's key for measuring and analyzing business activities.

43. What is a Dimension Table?

Ans. A Dimension Table in data warehousing forms part of the star, snowflake, or starflake schemas. It contains measurements and context for the data in the fact table and plays a vital role in dimensional modeling.

44. How to connect the foreign key columns in dimension and fact table.

Ans. In data warehousing, connecting foreign key columns involves linking primary keys of dimension tables with corresponding foreign keys in fact tables, and vice versa, establishing relational integrity.

45. Describe different methods to load dimension tables.

Ans. Loading data into dimension tables can be done using Conventional Loading, where data integrity checks are performed beforehand, or Direct Loading, where data is loaded first and checked for integrity afterward.

46. Name various objects that can’t be used in a mapplet.

Ans. In Informatica, certain objects are not compatible with Mapplets, including COBOL source definitions, target definitions, XML source definitions, joiner transformations, and others.

47. Define different ways used in Informatica to migrate from one environment to another.

Ans. Migrating environments in Informatica can be accomplished by exporting and importing repositories, using deployment groups, copying objects or folders, or transferring mappings as XML files.

48. What are the ways for deleting duplicate records in Informatica?

Ans. To eliminate duplicate records in Informatica, methods like using 'select distinct' in source qualifiers, applying specific SQL queries, or employing group by and aggregator functions are effective.

49. Differentiate between variable and mapping parameters.

  • Ans. Mapping parameters in Informatica are static values set prior to a session, while mapping variables are dynamic, changing their values during a session and storing the updated value for subsequent sessions.

50. Describe various repositories that can be generated using Informatica Repository Manager.

Ans. Informatica Repository Manager can create various types of repositories, including Global Repositories for shared objects, Local Repositories for specific domain use, Standalone Repositories for independent operations, and Version Control Repositories for object versioning.

51. How to find all the invalid mappings in a folder?

Ans. To identify invalid mappings in a folder in Informatica, a specific SQL query can be executed, targeting mappings that fail to meet validation criteria in the repository.

52. Name various data movement modes in Informatica.

Ans. In Informatica, data movement modes include ASCII Mode for standard data handling and Unicode Mode for managing data with diverse character sets, accommodating global data integration needs.

53. What is OLTP?

Ans. OLTP, or Online Transaction Processing, involves managing real-time data transactions, capturing and processing transactional data effectively in a database system.

54. Describe the parallel degree of data loading properties in MDM.

Ans. In Informatica MDM, the parallel degree of data loading properties determines the level of parallelism during data loading, affecting performance based on database CPU and memory resources.

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55. Explain various types of LOCK used in Informatica MDM 10.1.

Ans. Informatica MDM 10.1 utilizes Exclusive LOCK for single-user access and Write LOCK for multi-user concurrent access to metadata, ensuring controlled and secure data management.

56. What is the expiration module of automatic lock-in Informatica MDM?

Ans. The automatic lock expiration module in Informatica MDM refreshes the hub console every 60 seconds, releasing locks held by users if they switch databases or terminate the console.

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57. Name the tool which does not require Lock in Informatica MDM.

Ans. In Informatica MDM, tools like the Merge Manager, Audit Manager, Data Manager, and Hierarchy Manager do not require a locking mechanism, facilitating uninterrupted data management workflows.

58. Name various tools that require LOCK in Informatica MDM.

Ans. Tools in Informatica MDM that necessitate locks for database configuration changes include Tool Access, Message Queues, Security Providers, Databases, Users, and the Repository Manager.

59. Name the tables that are linked with staging data in Informatica MDM.

Ans. Tables associated with staging data in Informatica MDM include the Raw Table, Landing Table, Rejects Table, and Staging Table, each serving distinct roles in the staging process.

60. What is OLAP?

Ans. OLAP (Online Analytical Processing) software performs multidimensional analysis on large volumes of data. It collects, processes, manages, and presents data for analysis and management. 

61. What are the processes involved in Informatica MDM?

Ans. The data from different sources undergoes complex processing and the processes in Informatica include:

  • Landing - the data is acquired from the source system and pushed into the MDM landing tables. 
  • Staging - all the data in the landing tables is cleansed, standardised and then pushed into the MDM staging tables. 
  • Load - the data from the staging table is collected and loaded into the BO table.
  • Tokenization - the tokenization process is used after the configuration of match rules to generate match tokens. 
  • Match - the match process plays an integral role in helping match the records.
  • Merge or Consolidation - all the records that have been matched are consolidated during the merge process.

62. What is a stage process?

Ans. The stage process refers to moving data from landing tables to stage tables, using specific stage mappings. This process includes data cleansing and standardization.

Conlusion:

This article is designed to prepare candidates for common interview questions, enhancing their knowledge and confidence. Readers are encouraged to suggest any new questions faced during their interview for further updates.

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As a senior Technical Content Writer for HKR Trainings, Gayathri has a good comprehension of the present technical innovations, which incorporates perspectives like Business Intelligence and Analytics. She conveys advanced technical ideas precisely and vividly, as conceivable to the target group, guaranteeing that the content is available to clients. She writes qualitative content in the field of Data Warehousing & ETL, Big Data Analytics, and ERP Tools. Connect me on LinkedIn.

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